Define the common options that are used in both training and test.
(self, parser)
| 21 | self.cmd_line = cmd_line.split() |
| 22 | |
| 23 | def initialize(self, parser): |
| 24 | """Define the common options that are used in both training and test.""" |
| 25 | # basic parameters |
| 26 | parser.add_argument('--dataroot', default='placeholder', help='path to images (should have subfolders trainA, trainB, valA, valB, etc)') |
| 27 | parser.add_argument('--name', type=str, default='experiment_name', help='name of the experiment. It decides where to store samples and models') |
| 28 | parser.add_argument('--easy_label', type=str, default='experiment_name', help='Interpretable name') |
| 29 | parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0 0,1,2, 0,2. use -1 for CPU') |
| 30 | parser.add_argument('--checkpoints_dir', type=str, default='./checkpoints', help='models are saved here') |
| 31 | # model parameters |
| 32 | parser.add_argument('--model', type=str, default='dcl', help='chooses which model to use.') |
| 33 | parser.add_argument('--input_nc', type=int, default=3, help='# of input image channels: 3 for RGB and 1 for grayscale') |
| 34 | parser.add_argument('--output_nc', type=int, default=3, help='# of output image channels: 3 for RGB and 1 for grayscale') |
| 35 | parser.add_argument('--ngf', type=int, default=64, help='# of gen filters in the last conv layer') |
| 36 | parser.add_argument('--ndf', type=int, default=64, help='# of discrim filters in the first conv layer') |
| 37 | parser.add_argument('--netD', type=str, default='basic', choices=['basic', 'n_layers', 'pixel', 'patch', 'tilestylegan2', 'stylegan2'], help='specify discriminator architecture. The basic model is a 70x70 PatchGAN. n_layers allows you to specify the layers in the discriminator') |
| 38 | parser.add_argument('--netG', type=str, default='resnet_9blocks', choices=['resnet_9blocks', 'resnet_6blocks', 'unet_256', 'unet_128', 'stylegan2', 'smallstylegan2', 'resnet_cat'], help='specify generator architecture') |
| 39 | parser.add_argument('--n_layers_D', type=int, default=3, help='only used if netD==n_layers') |
| 40 | parser.add_argument('--normG', type=str, default='instance', choices=['instance', 'batch', 'none'], help='instance normalization or batch normalization for G') |
| 41 | parser.add_argument('--normD', type=str, default='instance', choices=['instance', 'batch', 'none'], help='instance normalization or batch normalization for D') |
| 42 | parser.add_argument('--init_type', type=str, default='xavier', choices=['normal', 'xavier', 'kaiming', 'orthogonal'], help='network initialization') |
| 43 | parser.add_argument('--init_gain', type=float, default=0.02, help='scaling factor for normal, xavier and orthogonal.') |
| 44 | parser.add_argument('--no_dropout', type=util.str2bool, nargs='?', const=True, default=True, |
| 45 | help='no dropout for the generator') |
| 46 | parser.add_argument('--no_antialias', action='store_true', help='if specified, use stride=2 convs instead of antialiased-downsampling (sad)') |
| 47 | parser.add_argument('--no_antialias_up', action='store_true', help='if specified, use [upconv(learned filter)] instead of [upconv(hard-coded [1,3,3,1] filter), conv]') |
| 48 | # dataset parameters |
| 49 | parser.add_argument('--dataset_mode', type=str, default='unaligned', help='chooses how datasets are loaded. [unaligned | aligned | single | colorization]') |
| 50 | parser.add_argument('--direction', type=str, default='AtoB', help='AtoB or BtoA') |
| 51 | parser.add_argument('--serial_batches', action='store_true', help='if true, takes images in order to make batches, otherwise takes them randomly') |
| 52 | parser.add_argument('--num_threads', default=4, type=int, help='# threads for loading data') |
| 53 | parser.add_argument('--batch_size', type=int, default=1, help='input batch size') |
| 54 | parser.add_argument('--load_size', type=int, default=286, help='scale images to this size') |
| 55 | parser.add_argument('--crop_size', type=int, default=256, help='then crop to this size') |
| 56 | parser.add_argument('--max_dataset_size', type=int, default=float("inf"), help='Maximum number of samples allowed per dataset. If the dataset directory contains more than max_dataset_size, only a subset is loaded.') |
| 57 | parser.add_argument('--preprocess', type=str, default='resize_and_crop', help='scaling and cropping of images at load time [resize_and_crop | crop | scale_width | scale_width_and_crop | none]') |
| 58 | parser.add_argument('--no_flip', action='store_true', help='if specified, do not flip the images for data augmentation') |
| 59 | parser.add_argument('--display_winsize', type=int, default=256, help='display window size for both visdom and HTML') |
| 60 | parser.add_argument('--random_scale_max', type=float, default=3.0, |
| 61 | help='(used for single image translation) Randomly scale the image by the specified factor as data augmentation.') |
| 62 | # additional parameters |
| 63 | parser.add_argument('--epoch', type=str, default='latest', help='which epoch to load? set to latest to use latest cached model') |
| 64 | parser.add_argument('--verbose', action='store_true', help='if specified, print more debugging information') |
| 65 | parser.add_argument('--suffix', default='', type=str, help='customized suffix: opt.name = opt.name + suffix: e.g., {model}_{netG}_size{load_size}') |
| 66 | |
| 67 | # parameters related to StyleGAN2-based network |
| 68 | parser.add_argument('--stylegan2_G_num_downsampling', |
| 69 | default=1, type=int, |
| 70 | help='Number of downsampling layers used by StyleGAN2Generator') |
| 71 | |
| 72 | self.initialized = True |
| 73 | return parser |
| 74 | |
| 75 | def gather_options(self): |
| 76 | """Initialize our parser with basic options(only once). |